Prediction performance of the EGA-BPNN model with different numbers of hidden layer nodes.

<p>Prediction performance of the EGA-BPNN model with different numbers of hidden layer nodes.</p>

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Bibliographic Details
Main Author:	Xiying Wang (4859998) (author)
Published:	2025
Subjects:	Medicine Ecology Science Policy Space Science Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Information Systems not elsewhere classified sup >&# 8722 hidden layer increases global search ability complex environmental factors comparative experiments compare bp neural network 68 × 10 66 × 10 53 × 10 38 × 10 predict irrigation flow mean squared error research outcomes contribute irrigation flow prediction absolute relative error div >< p 4 </ sup bpnn model exhibits bpnn model achieves model prediction accuracy bpnn using single relative error flow prediction prediction accuracy bpnn model research topic model ’ model performance traditional bpnn standalone bpnn bpnn principles work explores smart agriculture sample dependency revealing issues results reveal reliable basis positive impact local optimization local optima initial values genetic algorithm decreasing trend artificial intelligence agricultural fields 11 reduction 09 %.
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